Touch sensing systems (“touch systems”) are in widespread use in a variety of applications. Typically, the touch systems are actuated by a touching object such as a finger or stylus, either in direct contact or through proximity (i.e. without contact) with a touch surface. Touch systems are for example used as touch pads of laptop computers, in control panels, and as overlays to displays on e.g. hand held devices, such as mobile telephones. A touch system that is overlaid on or integrated in a display is also denoted a “touch screen”. Many other applications are known in the art.
To an increasing extent, touch systems are designed to be able to detect two or more touches simultaneously, this capability often being referred to as “multi-touch” in the art. There are numerous known techniques for providing multi-touch sensitivity, e.g. by using cameras to capture light scattered off the point(s) of touch on a panel, or by incorporating resistive wire grids, capacitive sensors, strain gauges, etc into a panel.
US2004/0252091 discloses an alternative technique which is based on frustrated total internal reflection (FTIR). Diverging light sheets are coupled into a panel to propagate inside the panel by total internal reflection. When an object comes into contact with a surface of the panel, two or more light sheets will be locally attenuated at the point of touch. Arrays of light sensors are located around the perimeter of the panel to detect the received light for each light sheet. A coarse reconstruction of the light field across the panel surface is then created by geometrically back-tracing and triangulating all attenuations observed in the received light. This is stated to result in data regarding the position and size of each contact area.
US2009/0153519 discloses a panel capable of conducting signals on a plurality of signal paths. A “tomograph” is positioned adjacent the panel with signal flow ports arrayed around the border of the panel at discrete locations. Signal values measured at the signal flow ports for the different signal paths are arranged in a sinogram (b) and tomographically processed to generate a representation (x) of the conductivity on the panel in a grid of pixels, whereby touching objects on the panel surface can be detected. The presented technique for tomographic reconstruction is based on a linear model of the tomographic system, Ax=b. The system matrix A is calculated at factory, and its pseudo inverse A−1 is calculated using Truncated SVD algorithms and operated on the sinogram b of measured signal values to yield the conductivity for the grid of pixels: x=A−1b. Thereby, the conductivity of each pixel is given by a linear combination of the measured signal values. US2009/0153519 also mentions that the signal values of certain signal paths may be discarded or not measured at all, e.g. signal values for signal paths that are too short or known to produce weak signals.
The technique presented in US2009/0153519 is merely a straight-forward implementation of well-known tomographic algorithms for reconstructing an image of a cross-section through an attenuating medium based on projection measurements through the attenuating medium. Many tomographic algorithms are known in the art, e.g. Filtered Back Projection (FBP), FFT-based algorithms, ART (Algebraic Reconstruction Technique), SART (Simultaneous Algebraic Reconstruction Technique), etc. On a general level, the tomographic algorithms apply a back projection or inversion function on the projection measurements to produce reconstruction values that represent the attenuating medium. The inversion function may operate in either the spatial domain or the Fourier domain to provide a solution to a linear system of equations. Generally, in all of the above-mentioned tomographic algorithms, the inversion function is designed to generate the reconstruction value of a pixel in the image as a linear combination of the projection measurements through this pixel, as well as at least part of the projection measurements through other pixels. For further details, reference is made to “The Mathematics of Computerized Tomography”, by F Natterer, 2001, Chapter V: “Reconstruction algorithms”.
Conventionally, tomographic algorithms are designed for medical imaging purposes and operate on a large number of projection measurements at specific angles to the attenuating medium, where the projection measurements are produced by a rotating measurement system. Touch systems, on the other hand, have a fixed measurement system (cf. the above-mentioned signal ports) which produces a limited number of projection measurements at signal paths that are generally mismatched to the tomographic algorithms. This may introduce reconstruction errors into the resulting image and make it difficult to properly detect touching objects. Reconstruction errors may e.g. make it difficult to detect weakly interacting objects in presence of strongly interacting objects, or to separately detect objects in proximity to each other on the touch surface.
In addition, touch systems typically need to operate to generate the image in real time and at high repetition rate, e.g. 10-100 Hz.
There is thus a general need to develop improved techniques for detecting objects on a touch surface based on projection measurements through a signal conducting panel.